Nicolas Anchaño Senior Data Engineer

Senior Site Reliability Engineer

Chainlink Labs

Apr 2024 - Current (2 years 5 months)

Drive ongoing modernization of the observability platform towards an OTEL based VictoriaMetrics/Traces/Logs stack, designing ingestion paths, retention strategy, query compatibility and alerting validation; while maintaining production telemetry continuity and minimizing work on product teams. Own, scale and improve company-wide observability platform (Prometheus, Loki, Thanos, OTEL, Alertmanager), ingesting 1M+ metric samples/sec and 650K log lines/sec across 3 environments and 18 clusters, with 1.5PB+ historical data in S3; defined SLIs (metric ingestion success rate, query error rate, alert evaluation latency) and enforced >=99.99% availability SLO. Lead cloud cost savings initiatives for the entire Data Platform pillar in both AWS and

Senior Data Engineer

Medialab

Jun 2021 - Apr 2024 (2 years 11 months)

Architected and deployed Go-based event processing services handling 12K req/sec on Kubernetes and Cloud Run, centralizing data ingestion across business units and eliminating duplicated data processing paths. Built and operated event-driven streaming infrastructure processing 15+ TB of events daily, implementing standardized Terraform-based IaC and monitoring to improve pipeline reliability and concurrency safety. Developed automated data pipeline frameworks using Python, Airflow, and Kubernetes that generate hundreds of standardized DAGs, reducing new pipeline development time by 80% and improving operational consistency. Deployed ML-driven classification, vectorization, and recommendation workloads through Kubernetes-based Airflow DAG

Senior Data Engineer

Medialab

Jun 2021 - Mar 2023 (1 year 10 months)

- Diseñar y desarrollar microservicios backend y APIs con Go y Kubernetes para la validación, tratamiento de datos y exposición de los mismos a diferentes usuarios. - Implementar y mantener data pipelines con Python, Airflow y Kubernetes para la extracción, transformación y carga de datos de gran variedad de fuentes hacia distintos servicios. - Colaborar con el equipo de data scientists para implementar modelos de machine learning y soluciones de inteligencia artificial. Poner en producción los pipelines, microservicios y productions de inteligencia artificial mencionados, incluyendo la creacion de infraestructura, construyendo procesos de CI/CD con Terraform y GitHub Actions.

Data Engineer

Accenture Argentina

Feb 2021 - Jun 2021 (5 months)

- Liderar el proceso técnico de migración de Data Pipelines on-premise a cloud, determinando si hay necesidad de refactory o no. - Planear la nueva arquitectura en cloud y definir las herramientas a utilizar de acuerdo a cada caso, teniendo en cuenta integración de datos, costos y automatización. - Desarrollar procesos de ETL: extraer y transformar datos, estructurados y no estructurados, con Python, Spark, Hive y Bash, y cargarlos en bases de datos SQL (Redshift) y NoSQL (DynamoDB) sobre AWS.

Senior Data Engineer

Accenture Argentina

Feb 2021 - Jun 2021 (5 months)

Led technical migration of legacy mainframe and Hadoop systems to AWS for a major American energy company, successfully migrating 50+ data pipelines processing 10TB daily from on-premise infrastructure to cloud-native architecture using EMR, S3, and DynamoDB Architected cloud data processing solutions by refactoring legacy Scala Spark code to PySpark and designing EMR-based workflows, overcoming complex access controls and legacy system constraints to improve processing performance and scalability Managed end-to-end migration execution including infrastructure planning, code modernization, and production deployments, delivering the first migration batch within 3-month timeline while maintaining data integrity and business continuity

Data Scientist

Performics

Sep 2020 - Feb 2021 (6 months)

Developed statistical and machine learning models for data analysis to evaluate advertisement campaign effectiveness, from organizing datasets to parameter tuning and defining models. Built applications and dashboards to present results and deliver aggregate value to the business, providing insights on forecasting, churn, and other key metrics. Collaborated on data engineering tasks to improve data quality and availability, driving automation as well as efficiency in terms of cost and time.

Data Engineer

ITE CONSULT

Aug 2018 - Sep 2020 (2 years 2 months)

- Dirigir el proceso de ETL; extrayendo los datos de diversas bases de datos SQL o APIs, limpiarlos, transformarlos, y recargarlos usando Python and GCP para su uso en reportes, tablas y gráficos. - Desarrollar software en Python para la automatización de las diversas tareas descriptas: corrida de modelos, subida de resultados, descarga y recarga de tablas, entre otras. - Armar modelos de finance, sales y demand planning; tanto la parte técnica de arreglo, análisis y cruce de datos maestros y transaccionales como también su visualización e interactividad, en GCP y SAP Analytics Cloud.

Data Engineer

ITE CONSULT

Aug 2018 - Sep 2020 (2 years 2 months)

Conducted the ETL process: extracted data from various SQL databases and APIs, cleaned and transformed it, and reloaded it into cloud services using Python and Google Cloud Platform, enabling its use in reports, tables, and graphics. Designed software in Python to automate these tasks, including running models, uploading results, downloading and reuploading SQL tables, among others. Created finance, sales, and demand planning models, covering both the technical aspects—data cleaning, analysis, and integration of master and transactional data—and their visualization and interactivity on GCP and SAP Analytics Cloud.

Nicolas Anchaño

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